CSV: Visual Support for Understanding Card Synergy in Digital Collectible Card Games

Yicheng Xue, Hiroshi Hosobe

2025

Abstract

Digital Collectible Card Games (DCCGs) are a popular genre of video games that typically feature a continuously expanding pool of cards, requiring players to construct their own decks in order to play. However, the complexity of the game rules and the large number of cards cause information overload, resulting in various issues. In this research, we propose a framework to help users overcome information overload by providing a clear visualization of card synergies using 3D graphs. We employ text analysis and the co-occurrence network to calculate synergy scores between cards, and then represent the cards as nodes and their synergies as edges in our integrative 3D graph. In our experiment, we collected the decks of elite players as our dataset and visualized the synergies among approximately 1,000 cards in “Yu-Gi-Oh! Master Duel”. To evaluate our framework, we conducted a questionnaire survey and a usability test with people experienced in playing DCCGs. The results indicate that our framework effectively assists users in deck construction and understanding of the game, and also provide valuable insights for the further development into a full-scale supporting tool.

Paper Citation

in Harvard Style

Xue Y. and Hosobe H. (2025). CSV: Visual Support for Understanding Card Synergy in Digital Collectible Card Games. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: HUCAPP; ISBN 978-989-758-728-3, SciTePress, pages 611-618. DOI: 10.5220/0013256900003912

in Bibtex Style

@conference{hucapp25,
author={Yicheng Xue and Hiroshi Hosobe},
title={CSV: Visual Support for Understanding Card Synergy in Digital Collectible Card Games},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: HUCAPP},
year={2025},
pages={611-618},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013256900003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: HUCAPP
TI - CSV: Visual Support for Understanding Card Synergy in Digital Collectible Card Games
SN - 978-989-758-728-3
AU - Xue Y.
AU - Hosobe H.
PY - 2025
SP - 611
EP - 618
DO - 10.5220/0013256900003912
PB - SciTePress